Daylighting and energy consumption in museums and bridging the gap by multi-objective optimization

被引:0
|
作者
Ismail, Mohamed Mostafa R. [1 ,2 ]
Nessim, Ashraf [1 ]
Fathy, Fatma [1 ]
机构
[1] Ain Shams Univ, Dept Architecture, Cairo, Egypt
[2] Ain Shams Univ, Fac Archeol, Dept Architectural Heritage Restorat & Conservat, Cairo, Egypt
关键词
Energy; Daylighting; Architectural intervention; Smart systems; Multi-objective optimization; Museums; Sustainability;
D O I
10.1016/j.asej.2024.102944
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Museums environment is complicated and defined by indoor air quality, thermal and lighting comfort. Artifacts deterioration is factored by extreme conditions of thermal exposure or excessive lighting. With high control required for exposed old monuments and visitor comfort, museums energy systems reach extreme levels. In this paper, we aim to find the gap in museums high energy loads and reach solutions through architectural design. The paper studies comparison results for different techniques in fifty recent case studies to identify the specific factors that matter most to museum buildings. These factors are implemented simultaneously on one base model in three climatic states by multi-objective optimization. The best option will showcase each climate optimum conditions. The paper introduces optimum architectural procedures optimizing sDA and ASE to minimum 70% and maximum 10% respectively while decreasing thermal load. The results help architects and policy makers achieve daylighting and energy optimization in museums through architecture.
引用
收藏
页数:21
相关论文
共 50 条
  • [1] Multi-objective optimization of daylighting performance and energy consumption of educational buildings in different climatic zones of China
    Liu, Jixin
    Li, Zhe
    Zhong, Qikang
    Wu, Jiade
    Xie, Liang
    JOURNAL OF BUILDING ENGINEERING, 2024, 95
  • [2] Multi-objective optimization for energy consumption, daylighting and thermal comfort performance of rural tourism buildings in north China
    Zhu, Li
    Wang, Binghua
    Sun, Yong
    BUILDING AND ENVIRONMENT, 2020, 176
  • [3] Intelligent optimization: A novel framework to automatize multi-objective optimization of building daylighting and energy performances
    Dong, Yuhan
    Sun, Cheng
    Han, Yunsong
    Liu, Qianqian
    JOURNAL OF BUILDING ENGINEERING, 2021, 43
  • [4] Multi-objective optimization of building-integrated microalgae photobioreactors for energy and daylighting performance
    Talaei, Maryam
    Mahdavinejad, Mohammadjavad
    Azari, Rahman
    Prieto, Alejandro
    Sangin, Hamed
    JOURNAL OF BUILDING ENGINEERING, 2021, 42
  • [5] Multi-Objective Optimization of Energy Consumption of GUIs in Android Apps
    Linares-Vasquez, Mario
    Bavota, Gabriele
    Bernal-Cardenas, Carlos
    Di Penta, Massimiliano
    Oliveto, Rocco
    Poshyvanyk, Denys
    ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY, 2018, 27 (03)
  • [6] Multi-objective optimization of machining parameters considering energy consumption
    Wang, Qiulian
    Liu, Fei
    Wang, Xianglian
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2014, 71 (5-8): : 1133 - 1142
  • [7] Multi-objective optimization of building envelope for energy consumption and daylight
    Lartigue, B.
    Lasternas, B.
    Loftness, V.
    INDOOR AND BUILT ENVIRONMENT, 2014, 23 (01) : 70 - 80
  • [8] Multi-objective optimization of machining parameters considering energy consumption
    Qiulian Wang
    Fei Liu
    Xianglian Wang
    The International Journal of Advanced Manufacturing Technology, 2014, 71 : 1133 - 1142
  • [9] Multi-objective optimization of residential building energy consumption, daylighting, and thermal comfort based on BO-XGBoost-NSGA-II
    Wu, Chengjin
    Pan, Haize
    Luo, Zhenhua
    Liu, Chuan
    Huang, Hulongyi
    BUILDING AND ENVIRONMENT, 2024, 254
  • [10] Simplified Energy Model and Multi-Objective Energy Consumption Optimization of a Residential House
    Mrazek, Michal
    Honc, Daniel
    Sanseverino, Eleonora Riva
    Zizzo, Gaetano
    APPLIED SCIENCES-BASEL, 2022, 12 (20):